Systems and methods for dynamically replacing code objects for code pushdown

ABSTRACT

The present application is directed towards systems and methods for automated analysis and transformation of applications and automated pushdown of code from application layer to database layer, or from a data-to-code to code-to-data paradigm, including analyzing and extracting application layer code, relocating to and restructuring the code for the database layer, optimizing the code for better performance at the database layer, and adding communication interconnections between other applications and the pushed down code.

FIELD OF THE DISCLOSURE

The present application generally relates to analyzing, upgrading, andmodernizing an application. In particular, the present applicationrelates to systems and methods for automatically replacing codeconstructs with appropriate mappings and/or retaining parameter mappingfor use in code-to-data paradigms.

BACKGROUND OF THE DISCLOSURE

Many software applications may be modified or customized by users oradministrators to include additional functions, objects, databases, andcustomized code. When the underlying software application is upgraded toa new version, in many instances, the modified or customized functions,objects, databases, and code of the prior, obsolete version may beincompatible with the new version. Rewriting the modified or customizedfunctions, objects, databases, and/or code may be time consuming andexpensive.

BRIEF DESCRIPTION OF THE FIGURES

The details, objects, aspects, features, and advantages of variousembodiments of the invention are set forth in the description below andaccompanying drawings, in which:

FIG. 1A is a block diagram of an embodiment of a network environment fora client to access a server for analyzing and transforming anapplication from a source installation to a target installation;

FIG. 1B is a block diagram of an embodiment of a computing device;

FIG. 2A is a block diagram of an embodiment of a suite of applicationsfor analyzing and transforming an application from a source installationto a target installation;

FIG. 2B is a block diagram of an embodiment of an appliance foranalyzing and transforming an application from a source installation toa target installation;

FIG. 2C is block diagram of another embodiment of an appliance foranalyzing and transforming an application from a source installation toa target installation;

FIG. 2D is a block diagram of an embodiment of an analysis andtransformation of a source installation into a target installation;

FIG. 2E is a block diagram of an embodiment of a transformation process;

FIGS. 3A-B is a flow chart of an embodiment of a method of analyzing andtransforming an application from a source installation to a targetinstallation;

FIGS. 4A-B are block diagrams of data-to-code and code-to-data paradigmimplementations in a database management system; and

FIG. 4C is a flow chart of an implementation of a method of codepushdown.

The features and advantages of the present invention will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings, in which like reference charactersidentify corresponding elements throughout. In the drawings, likereference numbers generally indicate identical, functionally similar,and/or structurally similar elements.

DETAILED DESCRIPTION

The present application is directed towards systems and methods fordynamically modifying an application from a data-to-code paradigm to acode-to-data paradigm, sometimes referred to as code pushdown. The classof software systems and corresponding market segment referred to asEnterprise Resource Planning (ERP) is characterized by systems andapplications of extremely large breadth and scope of functionality,designed to coordinate, control, and support resources and informationrelated to business processes such as manufacturing, supply chainmanagement, financials, projects, human resources and customerrelationship management from a shared data store for an entireenterprise. The inherently large scope and complexity of ERP systemsposes significant challenges to modernization. Business owners mustbalance significant business and technical benefits of updating andmodernizing these vast systems against the considerable costs, risks,and disruption associated with large-scale modernization projections.

One example of an ERP system is the Systems, Applications, and Products(SAP) system developed by SAP AG of Walldorf, Germany. SAP uses aproprietary system architecture and programming language, the AdvancedBusiness Application Programming (ABAP) language, which includes theconcept of Logical Databases (LDBs). SAP is prominent in the market, andthis has spawned an industry sub-niche for providers of specializedservices and solutions related to SAP systems. Services and solutionsserving the SAP ERP market segment must be extremely knowledgeableabout, and closely aligned with, the underlying framework, architecture,and programming language of SAP systems, from both technical andbusiness perspectives.

One advantage of the SAP ERP environment is the ability of customers andconsultants to develop customized code, objects, reports, and interfacesfor specific business requirements. Referring briefly to FIG. 4A,illustrated is a block diagram of an embodiment of an ERP or databasemanagement system in accordance with a data-to-code paradigm. Themanagement system includes a user interface layer 400, comprisingpresentation and display or user interface software 406. The userinterface layer 400 communicates with applications in the applicationlayer 402, which includes management and orchestration functions 408 anddata processing or calculations 410, such as customized code andbusiness logic. The management system also includes a database layer404, including data 412. Although shown as a single system, in manyimplementations, these layers would have functionality distributedthrough a variety of systems. For example, a user interface layer may beprovided by a client terminal, while an application layer is provided byone or more application servers and a database layer is provided by oneor more data servers.

Under the traditional data-to-code paradigm, database access wasconsidered a bottleneck, particularly with large data sets anddistributed storage environments, and slow interconnections betweenenvironments. Additionally, while data servers were built for storage,they frequently had less processing capability than application servers,which were built particularly for performing large numbers of datacalculations. Accordingly, the business logic was implemented at theapplication layer, and data 412 would be transferred to an applicationserver for processing. This could be true even in instance in which alarge number of records were used as an input to a calculation with avery small output, such as calculating totals of cross-record data, oraggregating or counting values.

By contrast, FIG. 4B is a block diagram of a code-to-data paradigmimplementation in a database management system. At least some processing410′ is “pushed down” to the database layer 404, reducing the amount ofdata to be transferred between data servers and application servers. Theprocessing may be executed by the database server directly on the data“in place”, eliminating costly transfers.

While creating new implementations of code-to-data applications may berelatively easy, upgrading existing systems built on the data-to-codeparadigm may be more complicated, typically requiring significant manualrewriting of applications. In some aspects, the present invention isdirected to a method of automation in the analysis and transformation ofthese applications and automated pushdown of code, including analyzingand extracting application layer code, relocating to and restructuringthe code for the database layer, optimizing the code for betterperformance at the database layer, and adding communicationinterconnections between other applications and the pushed down code.

Accordingly, the present disclosure is directed to a system forautomated analysis and transformation of a system from a data-to-code toa code-to-data paradigm, moving customized code and business logic froman application layer to a database layer for optimized performance,particularly with calculations on large datasets. Although many of theexamples discussed below are tied to specific embodiments of systems,including ERP systems such as SAP, the disclosed systems and methods maybe applied to analyzing and transforming custom code in compliance withstandards and rules of any language and architecture.

For purposes of reading the description of the various embodimentsbelow, the following descriptions of the sections of the specificationand their respective contents may be helpful:

-   -   Section A describes a network environment and computing        environment which may be useful for practicing embodiments        described herein;    -   Section B describes embodiments of systems and methods for        analyzing and transforming an application from a source        installation to a target installation; and    -   Section C describes embodiments of systems and methods for        dynamically replacing code objects of an application for code        pushdown.

A. Network and Computing Environment

Prior to discussing the specifics of embodiments of the systems andmethods of the solution of the present disclosure, it may be helpful todiscuss the network and computing environments in which such embodimentsmay be deployed. Referring now to FIG. 1A, an embodiment of a networkenvironment 101 is depicted. In brief overview, the network environment101 comprises one or more systems 202-206 in communication with one ormore clients 208-210 (also generally referred to as remote machine(s)106) via one or more networks 104. Specifically shown are a bridgesystem 202, a source system 204, a target system 206, an analyzer client208, and a configuration client 210. In some embodiments, analyzerclient 208 and configuration client 210 may be the same client. In otherembodiments, bridge system 202 may be combined with analyzer client 208and/or configuration client 210. In yet another embodiment, bridgesystem 202 may be combined with either source system 204 or targetsystem 206. In some embodiments, a client 208-210 communicates with aserver 202-206 via an intermediary appliance (not shown), such as afirewall, a switch, a hub, a NAT, a proxy, a performance enhancingproxy, a network accelerator, a modem, or other network device of anyform or type.

As shown in FIG. 1A, the network 104 can be a local-area network (LAN),such as a company Intranet, a metropolitan area network (MAN), or a widearea network (WAN), such as the Internet or the World Wide Web. Althoughnot illustrated, network 104 may comprise one or more networks, coupledeither directly or via one or more intermediaries. In one embodiment,network 104 may be a private network. In another embodiment, network 104may be a public network. In some embodiments, network 104 may be acombination of one or more private networks and one or more publicnetworks. In some embodiments, clients 208-210 may be located at abranch office of a corporate enterprise communicating via a WANconnection over the network 104 to the systems 202-206 located at acorporate data center.

The network 104 may be any type and/or form of network and may includeany of the following: a point to point network, a broadcast network, awide area network, a local area network, a telecommunications network, adata communication network, a computer network, an ATM (AsynchronousTransfer Mode) network, a SONET (Synchronous Optical Network) network, aSDH (Synchronous Digital Hierarchy) network, a wireless network and awireline network. In some embodiments, the network 104 may comprise awireless link, such as an infrared channel or satellite band. Thetopology of the network 104 may be a bus, star, or ring networktopology. The network 104 and network topology may be of any suchnetwork or network topology as known to those ordinarily skilled in theart capable of supporting the operations described herein.

As shown in FIG. 1A, bridge system 202 may be a server or workstation,configured to include a solution manager 212 and/or a collection agent214, discussed in more detail below. As discussed above, althoughillustrated as a separate entity, bridge system 202 may be part of orcombined with either or both of analyzer client 208 and configurationclient 210.

Source system 204 may also be referred to as a source installation 204.In some embodiments, source system or source installation 204 maycomprise a server or workstation with an installation or configurationof a version of one or more applications. In one embodiment, the one ormore applications may also include an operating system. In anotherembodiment, the one or more applications may comprise an enterpriseresource planning (ERP) software, such as SAP Business Suite, SAP R/3,or SAP High-Performance Analytic Appliance (HANA), manufactured by SAPAG of Walldorf, Germany; Microsoft Dynamics, manufactured by MicrosoftCorporation of Redmond, Wash.; PeopleSoft, manufactured by OracleCorporation of Redwood Shores, Calif.; or any other type and form ofenterprise or manufacturing resource planning software. In anotherembodiment, the one or more applications may comprise any applicationthat comprises an installation in a predetermined state, andmodifications to objects from the predetermined state. In an example ofsuch an embodiment, a default installation of an ERP application may beinstalled on source installation 204. To account for specific needs ofthe business or industry, the installation may be modified, with customobjects, code, or functions for performing additional tasks or managingadditional resources not foreseen by the manufacturer of the ERPapplication. In another embodiment, the source system or sourceinstallation may comprise any type or form of application containingmodifications from an initial or default state.

An installation in a predetermined state may comprise any type and formof version, installation and/or state of configuration, modernization orcustomization of the same at any point during development, deployment ormaintenance of the application. In some embodiments, the predeterminedstate may be an initial or default installation of an application. Insome embodiments, the predetermined state may be the initial or defaultinstallation of a version of an application with a set of one or moreconfigurations, customizations or extensions. In some embodiments, thepredetermined state may be any version of an application with a set ofone or more configurations, customizations or extensions. In otherembodiments, the predetermined state may be any version that has beenupgraded or transformed using any of the systems and methods describedherein. In some embodiments, the predetermined state may be any point ofconfiguration or customization of a version of an application, whethercomplete, in-process or otherwise. For example, a predetermined state ofan application may be any set point in development, configuration orcustomization of an application. For example, the systems and methodsdescribed herein may be used to transform the configuration orcustomization during the development phases before the finalcustomizations or configurations are deployed for production.

Target system 206 may also be referred to as a target installation 206.In some embodiments, target system or target installation 206 maycomprise a server or workstation with an installation or configurationof a second version of one or more applications. In some embodiments,the second version may be similar to the first version of one or moreapplications on source system 204. As described above, source system 204may comprise custom objects, codes or functions. Using the methods andsystems described herein, target system 206 may be efficiently modifiedto comprise the custom objects, codes or functions of source system 204.In some embodiments, target system 206 may comprise additionalmodifications to allow the custom objects, codes or functions to executeor interact properly with the second version of the one or moreapplications. For example, a company with an existing source system 204may wish to upgrade to a new version of an underlying application on atarget system 206. The existing source system 204 may have modificationsand custom objects that the company wishes to include on target system206. In some embodiments, custom objects and code may be directlytransferred and will perform without error on target system 206.However, in many embodiments, the custom objects and code may needfurther modifications, due to differences between the underlyingapplication of target system 206 and source system 204.

Also shown in FIG. 1A are analyzer client 208 and configuration client210. Although shown as separate clients, in some embodiments, analyzerclient 208 and configuration client 210 may be combined, and/or may becombined with bridge system 202. Analyzer client 208 and configurationclient 210 may each be a workstation, client, or server. In someembodiments, analyzer client 208 is configured with or executes ananalysis agent 228 and/or transformer 230, described in more detailbelow. In some embodiments, configuration client 210 is configured withor executes a configuration agent 232 and/or a manual conversion agent234, described in more detail below.

The bridge system 202, source system 204, target system 206, analyzerclient 208 and configuration client 210 may be deployed as and/orexecuted on any type and form of computing device, such as a computer,network device or appliance capable of communicating on any type andform of network and performing the operations described herein.Furthermore, although only one each of systems 202-210 are illustrated,in many embodiments, the systems may each comprise one or more physicaland/or virtual machines, such as a server cloud, server farm, cloud ofvirtual machines executed by one or more physical machines, etc.

FIG. 1B is a block diagram of an exemplary computing device useful forpracticing the methods and systems described herein. The various devicesand servers may be deployed as and/or executed on any type and form ofcomputing device, such as a computer, network device or appliancecapable of communicating on any type and form of network and performingthe operations described herein. The computing device may comprise alaptop computer, desktop computer, virtual machine executed by aphysical computer, tablet computer, such as an iPad tablet manufacturedby Apple Inc. or Android-based tablet such as those manufactured bySamsung, Inc. or Motorola, Inc., smart phone or PDA such as aniPhone-brand/iOS-based smart phone manufactured by Apple Inc.,Android-based smart phone such as a Samsung Galaxy or HTC Droid smartphone, or any other type and form of computing device. FIG. 1B depicts ablock diagram of a computing device 150 useful for practicing anembodiment of the bridge system 202, source system 204, target system206, analyzer client 208, or configuration client 210. A computingdevice 150 may include a central processing unit 151; a main memory unit152; a visual display device 174; one or more input/output devices 179a-179 b (generally referred to using reference numeral 179), such as akeyboard 176, which may be a virtual keyboard or a physical keyboard,and/or a pointing device 177, such as a mouse, touchpad, or capacitiveor resistive single- or multi-touch input device; and a cache memory(not illustrated) in communication with the central processing unit 151,which may be connected via a bus 175.

The central processing unit 151 is any logic circuitry that responds toand processes instructions fetched from the main memory unit 152 and/orstorage 178. The central processing unit may be provided by amicroprocessor unit, such as: those manufactured by Intel Corporation ofSanta Clara, Calif.; those manufactured by Motorola Corporation ofSchaumburg, Ill.; those manufactured by Apple Inc. of Cupertino Calif.,or any other single- or multi-core processor, or any other processorcapable of operating as described herein, or a combination of two ormore single- or multi-core processors. Main memory unit 152 may be oneor more memory chips capable of storing data and allowing any storagelocation to be directly accessed by the microprocessor 151, such asrandom access memory (RAM) of any type. In some embodiments, main memoryunit 152 may include cache memory or other types of memory.

The computing device 150 may support any suitable installation device166, such as a floppy disk drive, a CD-ROM drive, a CD-R/RW drive, aDVD-ROM drive, tape drives of various formats, USB/Flash devices, ahard-drive or any other device suitable for installing software andprograms such as a social media application or presentation engine, orportion thereof. The computing device 150 may further comprise a storagedevice 178, such as one or more hard disk drives or redundant arrays ofindependent disks, for storing an operating system and other relatedsoftware, and for storing application software programs such as anyprogram related to the social media application or presentation engine.

Furthermore, the computing device 150 may include a network interface168 to interface to a Local Area Network (LAN), Wide Area Network (WAN)or the Internet through a variety of connections including, but notlimited to, standard telephone lines, LAN or WAN links (e.g., Ethernet,T1, T3, 56 kb, X.25), broadband connections (e.g., ISDN, Frame Relay,ATM), wireless connections, (802.11a/b/g/n/ac, BlueTooth), cellularconnections, or some combination of any or all of the above. The networkinterface 168 may comprise a built-in network adapter, network interfacecard, PCMCIA network card, card bus network adapter, wireless networkadapter, USB network adapter, cellular modem or any other devicesuitable for interfacing the computing device 150 to any type of networkcapable of communication and performing the operations described herein.

A wide variety of I/O devices 179 a-179 n may be present in thecomputing device 150. Input devices include keyboards, mice, trackpads,trackballs, microphones, drawing tablets, and single- or multi-touchscreens. Output devices include video displays, speakers, headphones,inkjet printers, laser printers, and dye-sublimation printers. The I/Odevices 179 may be controlled by an I/O controller 173 as shown in FIG.1B. The I/O controller may control one or more I/O devices such as akeyboard 176 and a pointing device 177, e.g., a mouse, optical pen, ormulti-touch screen. Furthermore, an I/O device may also provide storage178 and/or an installation medium 166 for the computing device 150. Thecomputing device 150 may provide USB connections to receive handheld USBstorage devices such as the USB Flash Drive line of devices manufacturedby Twintech Industry, Inc. of Los Alamitos, Calif.

The computing device 150 may comprise or be connected to multipledisplay devices 174 a-174 n, which each may be of the same or differenttype and/or form. As such, any of the I/O devices 179 a-179 n and/or theI/O controller 173 may comprise any type and/or form of suitablehardware, software embodied on a tangible medium, or combination ofhardware and software to support, enable or provide for the connectionand use of multiple display devices 174 a-174 n by the computing device150. For example, the computing device 150 may include any type and/orform of video adapter, video card, driver, and/or library to interface,communicate, connect or otherwise use the display devices 174 a-174 n. Avideo adapter may comprise multiple connectors to interface to multipledisplay devices 174 a-174 n. The computing device 150 may includemultiple video adapters, with each video adapter connected to one ormore of the display devices 174 a-174 n. Any portion of the operatingsystem of the computing device 150 may be configured for using multipledisplays 174 a-174 n. Additionally, one or more of the display devices174 a-174 n may be provided by one or more other computing devices, suchas computing devices 150 a and 150 b connected to the computing device150, for example, via a network. These embodiments may include any typeof software embodied on a tangible medium designed and constructed touse another computer's display device as a second display device 174 afor the computing device 150. One ordinarily skilled in the art willrecognize and appreciate the various ways and embodiments that acomputing device 150 may be configured to have multiple display devices174 a-174 n.

A computing device 150 of the sort depicted in FIG. 1B typicallyoperates under the control of an operating system, such as any of theversions of the Microsoft® Windows operating systems, the differentreleases of the Unix and Linux operating systems, any version of the MacOS® for Macintosh computers, any embedded operating system, anyreal-time operating system, any open source operating system, anyproprietary operating system, any operating systems for mobile computingdevices, or any other operating system capable of running on thecomputing device and performing the operations described herein.

The computing device 150 may have different processors, operatingsystems, and input devices consistent with the device. For example, inone embodiment, the computer 150 is an Apple iPhone or Motorola Droidsmart phone, or an Apple iPad or Samsung Galaxy Tab tablet computer,incorporating multi-input touch screens. Moreover, the computing device150 can be any workstation, desktop computer, laptop or notebookcomputer, server, handheld computer, mobile telephone, any othercomputer, or other form of computing or telecommunications device thatis capable of communication and that has sufficient processor power andmemory capacity to perform the operations described herein.

In some embodiments, a first computing device 100 a executes anapplication on behalf of a user of a client computing device 100 b. Inother embodiments, a computing device 100 a executes a virtual machine,which provides an execution session within which applications execute onbehalf of a user or a client computing devices 100 b. In one of theseembodiments, the execution session is a hosted desktop session. Inanother of these embodiments, the computing device 100 executes aterminal services session. The terminal services session may provide ahosted desktop environment. In still another of these embodiments, theexecution session provides access to a computing environment, which maycomprise one or more of: an application, a plurality of applications, adesktop application, and a desktop session in which one or moreapplications may execute.

B. Systems and Methods for Analyzing and Transforming an Applicationfrom a Source Installation to a Target Installation

FIG. 2A illustrates a block diagram of an embodiment of a suite ofapplications and data types for analyzing and transforming anapplication from a source installation to a target installation. Inbrief, FIG. 2A shows a source code optimizer 180, source code translator181, source code generator 182, test support engine 183, a data typeconverter 184, agents for data conversion 185 and data migration 186,and documentation 187. Together, blocks 180-187 comprise agents oftransformer 230. Similarly, statistics data 188, analysis engine 189,configuration agent 190 and interface business rules 191 comprise agentsof analysis agent 228. Meta-model 192 interacts with both the analysisagent 228 and transformer 230, and is established by parser engine 193.Additional data types are available, such as database information 194,source code 195, screen information 196, and business purposeinformation 197.

Shown in FIG. 2B is a block diagram of another embodiment of a systemfor analyzing and transforming an application from a source installationto a target installation. In brief, bridge system 202 may be configuredwith a solution manager 212, which may include a collection agent 214and may be configured with a remote function call (RFC) user account216A and a dialog user account 218A. Source system 204 may be configuredwith a source installation 220, which may include a collection plug-in222A. Source installation 220 may also be configured with an RFC useraccount 216B and a dialog user account 218B. Target system 206 may beconfigured with a target installation 224, which may include acollection plug-in 222B. Target installation 220 may also be configuredwith an RFC user account 216C, a dialog user account 218C, and a tooluser account 226. As shown, analyzer client 208 may be configured withan analysis agent 228 and a transformer 230. Configuration client 210may be configured with a configuration agent 232 and a manual conversionagent 234. In one embodiment, the collection agent 214 is able tocommunicate with collection plug-ins 222A and 222B via a network 104. Asshown, in some embodiments, analysis agent 228 and transformer 230 maybe configured to use RFC user accounts 216A-216C for communicating withsystems 202-206. Transformer 230 may also be configured to use tool useraccount 226. Additionally, in some embodiments, configuration agent 232and manual conversion agent 234 may be configured to use dialog useraccounts 218A-218C.

Still referring to FIG. 2B and in more detail, in some embodiments,bridge system 202 may be configured with or may execute a solutionmanager 212. In some embodiments, solution manager 212 may be anapplication, process, agent, function, routine, logic, or any type andform of executable instructions for snapshotting an installation. Insome embodiments, snapshotting or providing a snapshot of aninstallation comprises scanning and downloading components and/orassociations of an installation of an application, such as sourceinstallation 220. Snapshotting may also be referred to variously assaving, capturing, imaging, or storing an image, copy or an instance ofan installation. In additional embodiments, solution manager 212 mayfurther comprise functions for compressing a snapshotted image. In stillfurther embodiments, solution manager 212 may comprise or be associatedwith a storage medium capable of storing a snapshotted image. In oneembodiment, solution manager 212 may connect via a network to a sourceinstallation 220, described in more detail below. The solution manager212 may create a local copy of the entire source installation 220, or,in some embodiments, may parse the source installation 220 and copy aselected subset of the installation. For example, in one suchembodiment, solution manager 212 may parse the source installation 220for custom objects or code modified from a predetermined state of thesource installation, and store only a copy of the custom objects orcode. In another such embodiment, solution manager 212 may determine adifference between source installation 220 and target installation 224and store only the difference.

In many embodiments, solution manager 212 further comprisesfunctionality for identifying an object as being in a predeterminedstate or being in a modified state. For example, an object that has notbeen customized may, in some embodiments, be considered to be in apredetermined state. A predetermined state of an installation, in suchembodiments, may be the state of the installation prior to customizationor addition of custom objects, functions, or code. In furtherembodiments, solution manager 212 may comprise functionality foridentifying an object as an asset within-scope, such as a program, adatabase, or a screen, or an asset out-of-scope, such as atask-management system, a scheduler, an interface, a peripheral system,or a development environment. In yet further embodiments, solutionmanager 212 may comprise functionality for storing the identification ofobjects in a database, index, or list, which may be referred to as aworklist. In some embodiments, this worklist may be sent to the analyzerclient 208, described in more detail below.

In many embodiments, solution manager 212 further comprisesfunctionality for checking an object or code for compliance with alanguage syntax 282 and/or semantic rules 284. For example, an object orcode modified with custom programming may no longer be compliant with astandard syntax. In such a case, solution manager 212 may identify theobject as being not in compliance. In another embodiment, an object orcode may be modified, but still be compliant with a standard syntax. Insuch a case, solution manager 212 may identify the object as beingcompliant.

In some embodiments, as shown in FIG. 2B, solution manager 212 maycomprise or include a collection agent 214. Collection agent 214 may bean application, process, agent, function, routine, logic, or any typeand form of executable instructions for downloading or copying all orpart of a source installation 220 to bridge system 202. In someembodiments, collection agent 214 connects via a network to a collectionplugin 222A and/or collection plugin 222B, described in more detailbelow. Collection agent 214 may, in some embodiments, comprise functionsfor downloading source installation data as described above. In furtherembodiments, collection agent 214 and collection plugins 222A and 222Bmay be a standard application type or comply with a standard applicationtype and be executed by the source installation 220 and/or targetinstallation 224 without necessary modifications.

As shown in FIG. 2B, solution manager 212, source installation 220 andtarget installation 224 may include user accounts, such as RemoteFunction Call (RFC) users 216A-216C, Dialog users 218A-218C, and Tooluser 226. RFC users 216A-216C (referred to generally as RFC user(s) 216)may be an account with authentication features, such as a login name andpassword or other security methods, and privileges allowing the accountto get data from and insert data into source installation 220 and/ortarget installation 224. In some embodiments, data inserted or retrievedfrom an installation may comprise objects, code, or functions. In someembodiments, RFC users 216 may also be referred to as System orCommunication users. In further embodiments, the Dialog users 218A-218C(referred to generally as Dialog user(s) 218) may be an account withauthentication features, similar to those mentioned with regard to RFCusers 216, and privileges allowing the account to interact with programsand functions of source installation 220 and/or target installation 224.In some embodiments, a dialog user 218 may have fewer privileges or morelimited access than an RFC user 216. In additional embodiments, the Tooluser 226 may be an account with authentication features, similar tothose mentioned with regard to RFC users 216 and Dialog users 218, andprivileges allowing the account to use modification tools on targetinstallation 224.

As shown in FIG. 2B, source system 204 may comprise a sourceinstallation 220. As discussed above, in connection with the discussionof source system 204, source installation 220 may be an installation orconfiguration of a version of one or more applications. In oneembodiment, the one or more applications may comprise an enterpriseresource planning (ERP) software, such as SAP Business Suite or SAP R/3,manufactured by SAP AG of Walldorf, Germany; Microsoft Dynamics,manufactured by Microsoft Corporation of Redmond, Wash.; PeopleSoft,manufactured by Oracle Corporation of Redwood Shores, Calif.; or anyother type and form of enterprise or manufacturing resource planningsoftware. In another embodiment, the one or more applications maycomprise any application that comprises a default or initialinstallation in a predetermined state, and modifications to objects fromthe default state. In yet another embodiment, the source system orsource installation may comprise any type or form of applicationcontaining modifications from an initial or default state. As shown,source installation 220 may include one or more RFC users 216 and/ordialog users 218, discussed above.

Additionally, source installation 220 may include or be configured witha collection plugin 222A (generally referred to as a collection plugin222). Collection plugins 222 may comprise logic, services, hookingfunctions, routines, or any other type and form of function forgathering data of an installation, such as source installation 220 ortarget installation 224.

In some embodiments, collection plugins 222 may further comprisefunctions for snapshotting or recording an image of an installation asthe installation exists at a certain point in time. In some embodiments,collection plugins 222 may include the ability to push data over anetwork to collection agent 214, while in other embodiments, collectionagent 214 may pull data from the collection plugins.

Target system 206 may comprise a target installation 224. As discussedabove, in connection with the discussion of target system 206, targetinstallation 224 may be an installation or configuration of a second orsubsequent version of one or more applications, such as a versionsimilar to but different from a previous version of one or moreapplications on source system 204. As described above, sourceinstallation 220 may comprise custom objects, codes or functions. Usingthe methods and systems described herein, target installation 224 may beefficiently modified to comprise the custom objects, codes or functionsof source installation 220. In some embodiments, target installation 224may comprise additional modifications to allow the custom objects, codesor functions to execute or interact properly with the second version ofthe one or more applications. As shown, in some embodiments, targetinstallation 224 may include or comprise a collection plugin 222B, andmay include or be configured with accounts for RFC User 216C, DialogUser 218C, and Tool user 226, discussed above.

As shown, analyzer client 208 may comprise or include an analysis agent228 and/or a transformer 230. Analysis agent 228 may comprise one ormore applications, logic, functions, services, routines or executableinstructions of any type or form, for parsing a first and/or a secondinstallation of an application and creating a meta-model, described inmore detail below. In some embodiments, analysis agent 228 comprisesfunctions for downloading system objects identified by the solutionmanager 212 for transformation. In additional embodiments, analysisagent 228 comprises functions for parsing the source code of programs,databases, screens, task management systems, schedulers, interfaces,peripheral systems, development environments, and other libraries forkeywords, functions, objects, or code corresponding to a definedlanguage and syntax. In further embodiments, analyzer client 208 maycomprise functions for detecting syntax and language violations. In onesuch embodiment, analyzer client 208 may comprise functions tocategorize or identify the object, responsive to detected violations, asavailable for automatic upgrade, semi-automatic upgrade, or manualupgrade. In an additional embodiment, analyzer client 208 may comprisefunctionality for presenting the categorized objects and/or meta-modelto a user or administrator. In some such embodiments, presenting theobjects and or meta-model may comprise creating and presenting a report,and may include analysis of severity of required upgrades, expectedprocessing time, percentage of upgrade that may be performedautomatically, and/or cost to perform upgrading of the sourceinstallation.

In some of the embodiments described herein, a system or method may bedescribed as automatic, semi-automatic or manual. An automatic system ormethod may be such a system or method that performs any of the upgrades,transformations or conversion described herein without any user inputduring the upgrade, transformation or conversion or with a level of userinput below a predetermined threshold. A semi-automatic system or methodmay be such a system or method that performs any of the upgrades,transformations or conversion described herein with combination of alevel of automation and a level of user input during the upgrade,transformation or conversion below a predetermined threshold or within apredetermined threshold range. A manual system or method may be such asystem or method that performs any of the upgrades, transformations orconversion described herein without automation during the upgrade,transformation or conversion or with a level of automation below apredetermined threshold. In addition, in the description herein, objectsor code of a system may be referred to as comprising automatic code;comprising semi-automatic code; or comprising manual code. Similar tothe systems and methods described above, automatic code may be upgraded,transformed or converted without any user input during the upgrade,transformation, or conversion. Semi-automatic code may be upgraded,transformed or converted with a combination of a level of automation anda level of user input during the upgrade, transformation, or conversionbelow a predetermined threshold or within a predetermined thresholdrange. Manual code may be upgraded, transformed, or converted withoutautomation during the upgrade, transformation or conversion or with alevel of automation below a predetermined threshold.

Transformer 230 may comprise one or more applications, logic, functions,services, routines or executable instructions of any type or form, fortransforming a meta-model from one corresponding to one installation ofan application, to one corresponding to another installation of anapplication, such as between a first and second or subsequentinstallation of the application. In some embodiments, transforming ameta-model comprises applying rules for modifying an object from asyntax or code language associated with the first installation to asyntax or code language associated with the second installation. Forexample, in one embodiment, a first language may include a function forallowing text input into a database. The second language may include asimilar function, but add different possible text encodings, such asUnicode Transformation Format (UTF)-8 or punycode. In such anembodiment, the transformer 230 may apply a rule indicating to add adefault encoding type to the function. Thus, the object utilizing thefunction may then be used by the second installation with the secondlanguage and syntax. In some embodiments, transformer 230 furthercomprises functions for error checking transformed objects forcompliance with rules, language, and/or syntax standards. In anotherembodiment, transformer 230 further comprises functions for uploadingtransformed objects to target installation 224.

As shown, analysis agent 228 and transformer 230 may, in someembodiments, be configured to use RFC users 216A-216C on the solutionmanager 212, source installation 220, and target installation 224,respectively. This may enable analysis agent 228 and transformer 230 toretrieve and input data, code, and objects from and to these threesystems. In a further embodiment, transformer 230 may be configured touse tool user 226 on target installation 224. This may enabletransformer 230 to interact with system objects of the targetinstallation 224 that an RFC user may not be privileged to modify.

Also shown in FIG. 2B, configuration client 210 may, in someembodiments, comprise a configuration agent 232 and/or a manualconversion agent 234. In some embodiments, configuration agent 232 andmanual conversion agent 234 may be configured to use Dialog Users218A-218C, as shown. This may enable a user or administrator interactingwith configuration agent 232 and/or manual conversion agent 234 tofurther interact with solution manager 212, source installation 220,and/or target installation 224. In an embodiment not illustrated,configuration agent 232 and/or manual conversion agent 234 may alsocontrol or interact with analysis agent 228 and/or transformer 230 forthe purpose of modifying their settings.

Configuration agent 232 may comprise one or more applications, routines,services, functions or executable instructions of any form or type forconfiguring a rules engine 248, discussed in more detail below. In otherembodiments, configuration agent 232 may comprise functions forconfiguring solution manager 212, source installation 220, and/or targetinstallation 224. For example, in one such embodiment, configurationagent 232 may configure the solution manager 212 to only scan certaindatabases when snapshotting and categorizing objects.

Manual conversion agent 234 may comprise one or more applications,routines, services, functions or executable instructions of any form ortype for allowing a user or administrator to perform modifications toobjects categorized for semi-automatic or manual upgrade. In someembodiments, manual conversion agent 234 may present a dialog to a user,indicating the object to be upgraded, and a language or syntax issuethat could cause an error if the object is installed in targetinstallation 224. In some embodiments, manual conversion agent 234 mayalso present suggested modifications to the object, based on rulesapplied by the analysis agent 228. In further embodiments, manualconversion agent 234 may comprise functions for modifying the object,responsive to an instruction from the user. In a further embodiment,manual conversion agent 234 may comprise functions for uploading themodified object to target installation 224 and/or analyzer client 208.In one example embodiment, the manual conversion agent 234 may present adialog to a user indicating that an object of the source installation,when upgraded to the target installation, may perform an illegaloperation due to differences in syntax, such as dividing by a variablethat has been set to zero. The user may instruct the manual conversionagent 234 to make a modification, such as changing the value of thevariable, or directing the operation to a different variable.

Shown in FIG. 2C is another embodiment of a system for analyzing andtransforming an application from a source installation to a targetinstallation. In brief, source system 204 may comprise a sourceinstallation 220 and collection plugin, 222A, discussed above. Bridgesystem 202 may comprise a solution manager 212, discussed above, whichmay comprise an object analyzer 236, syntax checkers 238A-238B, unicodechecker 252 and post-processing agent 254. Analyzer client 208 maycomprise an analysis agent 228, which may further comprise a downloadengine 240 and an analysis engine 242. The analysis engine maycategorize code as automatic code 244A, semi-automatic code 244B, ormanual code 244C. Semi-automatic code 244B is passed to a rule engine246 configured on transformer 230. Rule engine 246 may apply rules tothe semi-automatic code 244B, and pass the code to conversion engine248. Automatic code 244A is passed from the analysis agent 228 to theconversion engine 248. Automatic code 244A and semi-automatic code 244Bare passed from the conversion engine 248 to the upload engine 250. Theupload engine 250 may upload converted automatic code 244A andsemi-automatic code 244B and unconverted manual code 244C to bridgesystem 202 and solution manager 212. Configuration client 210 maycomprise a configuration agent 232, which may configure rule engine 246of transformer 230, and a manual conversion agent 234, which mayinteract with post-processing agent 254 of solution manager 212.Although not shown, solution manager 212 may, in some embodiments,comprise an upload engine 250′ for transmitting processed and convertedcode to target installation 224 of target system 206.

Still referring to FIG. 2C and in more detail, solution manager 212 maybe configured with an object analyzer 236. In some embodiments, objectanalyzer 236 may comprise one or more applications, routines, services,functions or executable instructions of any form or type for analyzingan object obtained from collection plugin 222A. Although not shown,object analyzer 236 may further comprise functions for downloadingobjects identified by collection plugin 222A, such as a collection agent214 discussed above. Analyzing an object, as discussed above inconnection with solution manager 212, may comprise determining if theobject is compliant with a standard syntax and identifying the object,responsive to the determination, as compliant or non-compliant.Accordingly, and as shown, object analyzer 236 may interact with syntaxchecker 238A. In some embodiments, syntax checker 238A is a separateprocess, while in others, syntax checker 238A is a function orsubroutine of object analyzer 236. In still other embodiments, objectanalyzer 236 may be a function or subroutine of syntax checker 238A.

Syntax checker 238A may, in some embodiments, comprise one or moreapplications, routines, services, functions or executable instructionsof any form or type for comparing an object to a standard syntax. Insome embodiments, syntax checker 238A may comprise associated libraries,dictionaries, databases, or other data structures identifying syntax,functions, connectors, comments, instructions, code, or other objects ofone or more languages. For example, in one embodiment, syntax checker238A may include or be associated with a library defining objects in theAdvanced Business Application Programming (ABAP) designed by SAP AG ofWalldorf, Germany or using SAP HANA database artifacts. In anotherembodiment, syntax checker 238A may include a library defining objectsin Java, PHP, Python, Perl, SQL, or any other code language. In someembodiments, syntax checker 238A compares code within an objectidentified by or obtained from collection plugin 222A with code in thelibrary defining objects in a related language. In one exampleembodiment, syntax checker 238A receives an object from collectionplugin 222A that comprises a WRITE command. The syntax checker 238Acompares the object to a dictionary, which indicates that the WRITEcommand has been replaced by a WRITE TO command. Responsive to thiscomparison, the syntax checker 238A and/or object analyzer 236identifies the object as being non-compliant. In some embodiments, theidentification of an object as compliant or non-compliant may be in aseparate object, database, registry, or data structure, while in otherembodiments, the identification may be inserted into the object.

As shown, analysis agent 228 may include a download engine 240. Downloadengine 240 may comprise hardware and/or software components comprisingfunctions or executable instructions for downloading one or more objectsand/or identifications of objects as compliant or non-compliant fromsolution manager 212. In some embodiments, download engine 240 utilizesan RFC user account on solution manager 212 to download objects and/oridentifications, as discussed above.

Analysis engine 242 may, in some embodiments, comprise one or moreapplications, routines, services, functions or executable instructionsof any form or type for analyzing a capability of an object for upgradeto a target installation. For example, in one embodiment, an objectidentified as compliant with syntax of the language of the targetinstallation may be determined to be capable of automatic upgrading andbe identified as automatic code 244A. In one such embodiment, the objectmay need no modifications to be used by the target installation 224. Inanother such embodiment, the object may be identified as non-compliant,but need only minor modifications. For example, a comment indicator (“)used by the language of the source installation may be converted to acomment indicator (#) of the language the target installation withoutrequiring additional analysis. Similarly, a function that included novariables in the source installation, such as CLOSE may be converted toa function that includes optional variables in the target installation,such as CLOSE( ), without requiring additional analysis.

In another embodiment, analysis engine 242 may determine that anon-compliant object needs modifications that may be performedautomatically, but also needs modifications that require additionalinput, such as from a user or developer. This may be referred to assemi-automatic code. For example, in one embodiment, source installationobjects may include unicode characters, binary data, or a mix of binarydata. In one such embodiment, the target installation may include afunction that interacts with objects differently if they are binary orunicode. In such an embodiment, the analysis engine 242 may indicatethat some of the objects—those that are solely binary or unicode—may beconverted automatically, while objects that are mixed binary and unicodemay require a user to designate a mode. In such an embodiment, analysisengine 242 may indicate that the objects are semi-automatic code 244B.In another example, an object of the source installation may contain afunction that writes into a database. In one such embodiment, the targetinstallation may have more than one corresponding database. For example,source installation 220 may be a single user environment and have onlyone user database, while target installation 224 may be a multi-userenvironment. In some embodiments, the WRITE function may need to havemodifications that can be performed automatically, such as the additionof optional variables, or conversion to a WRITE TO statement, andmodifications that require input from a user, such as a path to aspecific directory or database in the multi-user environment of thetarget installation. Again, in such an embodiment, analysis engine 242may indicate that the objects are semi-automatic code 244B.

In another embodiment, analysis engine 242 may indicate that anon-compliant object may not be automatically or semi-automaticallyconverted to the language and/or syntax of the target installation 224,and may identify the object as manual code 244C. For example, a sourceinstallation object may use a function of the source installationlanguage that has been obsoleted or for which no corresponding functionexists in the target installation. In one such embodiment, the sourceinstallation object may read from a common memory. However, in thetarget installation, a common memory may have been replaced by isolatedmemory for privacy and security reasons. Accordingly, a READ COMMONfunction may be obsolete. Upgrading the function or an object using thefunction may, in such an embodiment, require further input not availableto the transformer 230. Responsive to this determination, analysisengine 242 may indicate that the object is manual code 244C.

In further detail of some of the embodiments of automated systems andmethods, an object of a source installation may have elements capable ofbeing upgraded, transformed, or converted to a language and syntax of atarget installation in a manner essentially independent of additionaluser, developer input, or other external control. These elements may bereferred to as automatic code, or automatic elements. In otherembodiments, an object may have elements that are incapable of beingupgraded, transformed, or converted to a language and syntax of a targetinstallation in a manner essentially independent of additional user,developer input, or other external control. These elements may bereferred to as manual code, or manual elements. In some embodiments, anobject may have a combination of both automatic elements and manualelements. In these embodiments, the ratio of elements that are capableof upgrade to elements in the object may used to determine an automationvalue for the object. In further embodiments, the automation value maybe compared to one or more thresholds. For example, if the automationvalue is equal to or less than a first threshold, the object may becategorized as manual. If the automation value is equal to or greaterthan a second threshold, the object may be categorized as automatic. Ifthe automation value is greater than the first threshold, but less thanthe second threshold, the object may be categorized as semi-automatic.In some embodiments, the first threshold may be set at zero, such thatan object may be categorized as manual only if it has no elements thatare capable of upgrade. In other embodiments, the second threshold maybe set at 1, such that an object may be categorized as automatic only ifit has no elements that are incapable of upgrade.

In a further embodiment, analysis engine 242 may create a meta-modelrepresentative of one or more objects of source installation 220. Themeta-model, in some embodiments, may be a syntax tree or abstract syntaxtree, and may represent relationships between the one or more objects ofthe source installation 220. In further embodiments, the meta-model maybe presented to a user in either a textual or graphical format. Inadditional embodiments, the meta-model may contain links tocorresponding source code of the one or more objects. In suchembodiments, an element in the meta-model may maintain or include areference to the original source file and line number. In furtherembodiments, the meta-model may also comprise a mapping of elements toobjects. The meta-model, in many embodiments, is a generic structure ofnodes, representing objects, and connectors, representing relationshipsbetween objects. In such embodiments, the meta-model has no syntaxitself and does not correspond to a specific language. In additionalembodiments, the meta-model may be used for processing and transformingobjects of the source installation into objects usable by the targetinstallation by finding and replacing patterns of connections. In someembodiments, the meta-model may map mutual relationships between objectsand characterize relationships as static or dynamic. In suchembodiments, a dynamic relationship between objects may change duringruntime. For example, a first object may depend alternately on a secondobject or a third object, responsive to an indicator within a fourthobject. When the indicator within the fourth object changes, the firstobject's dependency likewise changes. In other embodiments, themeta-model may map the relationship of objects to other system entities,such as data elements, operating system programs, system applicationprograms, transactions, environment settings, etc.

In some embodiments, analysis engine 242 may further comprise functionsfor inserting comments into source code of an object. These comments mayindicate suggested modifications to the object or potential errors orwarnings if the object is not further modified. For example, asdiscussed above, an object classified as semi-automatic code 244B mayrequire explicit identification of a working directory on the targetinstallation 224 that does not correspond to a directory existing onsource installation 220. Accordingly, analysis agent may add a commentto source code of the object indicating that a user should add explicitidentification of a working directory.

Analysis agent 242 may also, in some embodiments, comprise functions orexecutable instructions for generating a report and/or presenting thereport to a user. In these embodiments, the report may include analysisof ratios of automatic code, semi-automatic code, and manual code244A-244C, and may include descriptions of objects, likelihood of errorswhen transforming objects, estimated time and/or cost to transformobjects, and may include graphs, charts, and/or text. The report mayalso include a graphical or textual representation of the meta-model.

In additional embodiments, analysis agent 242 may be configured by auser with analysis rules. In these embodiments, analysis rules may beused to ensure that relevant information of interest to the user will beanalyzed while increasing efficiency of analysis by ignoring otherinformation. For example, rules may be set to allow analysis of justcompliant or non-compliant objects, rather than both sets of objects. Insome embodiments, rules may be selected to allow or disallow analysis ofobjects with unicode violations; analysis of objects that must changewith a transformation; analysis of obsoleted objects; analysis ofstatistics relating to the transformation, such as time and/or cost; andanalysis of transformations in specified languages, such as ABAP orJava. As referred to herein, unicode may be source code that complieswith syntax and language rules of the target installation. Althoughreferred to as unicode, it does not designate a specific embodiment ofunicode, such as the unicode standard for text. Rather, unicode maysimply refer to a language utilized by a target or source installation,such as Java, Python, Perl, PHP, or any other type and form of computinglanguage. In additional embodiments, analysis rules may be configured todetermine elements in the meta-model that match customer-definedcharacteristics, such as invocation of customer programs, use of text,specified modification dates, or any other type and form of informationrelating to or associated with an element.

In some embodiments, the analysis agent 242 may be used outside of atransformation context, to analyze custom code for objects in a sourceinstallation as they are being written. For example, the analysis agentmay be used to measure whether coding standards are being followed, bydetermining if an object may be classified as automatic code 244A fortransformation to a hypothetical target installation 224 that isidentical to source installation 220. A determination that the object issemi-automatic code 244B or manual code 244C may indicate thatadditional data should be added to the object, such as full path namesto directories or explicit indication of ASCII or binary data in astring.

In some embodiments, analysis engine 242 may be configured to detectobject clones. An object clone may be objects that are similar to eachother or similar to standard objects of the system provided by theapplication manufacturer. For example, one developer may create anobject, such as a current invoices database, with links to customer andsales databases, and another developer may create a similar currentinvoices database with a different name, due to miscommunication or lackof communication. Although the names are different, the two databasesare substantially similar. Future edits or modifications to onedatabase, however, may result in behavior unexpected to a developer whoonly knows about the other database. Accordingly, an analysis engine maybe configured to detect these clones and flag them for removal,modification, transformation, or deletion. In one embodiment, clones maybe detected by comparing normalized lines of the object code to create acommonality rating. If the commonality rating exceeds a predeterminedthreshold, the objects may be considered clones. Similarly, in someembodiments, analysis engine 242 may be configured to detect multipleversions of an object and include only the latest version of the objectfor transformation.

As shown in FIG. 2C, transformer 230 may include a rule engine 246. Insome embodiments, this rule engine may be configured by a configurationagent 232 on configuration client 210. Rule engine 246 may comprise anapplication, process, agent, function, routine, logic, or any type andform of executable instructions for modifying semi-automatic code 244Bin accordance with rules selected or configured by a user usingconfiguration agent 232. For example, as described above, an objectclassified as semi-automatic code 244B may require explicitidentification of a working directory on the target installation 224that does not correspond to a directory existing on source installation220. A user may select or configure a rule that identifies a workingdirectory to be added to the source code of the object. Rules engine 246may then apply this rule and modify the object accordingly. In someembodiments, selecting or configuring rules may be referred to asparameterization.

Objects that are identified as automatic code 244A or have been modifiedby the rules engine 246 may, in some embodiments, be sent to conversionengine 248. Conversion engine 248 may comprise an application, process,agent, function, routine, logic, or any type and form of executableinstructions for transforming objects from a language associated with asource installation to a language associated with a target installation.In many embodiments, rules engine 246 and conversion engine 248 maycomprise similar functionality, with conversion engine 248 applyingpreset or predetermined rules. In such embodiments, conversion engine248 may comprise or be associated with a database or data structurecontaining predetermined rules for a language or languages to allowconversion. Unlike rules configured by configuration agent 232 andapplied by rules engine 246, rules applied by the conversion engine 248may, in some embodiments, be unmodifiable by a user. In someembodiments, rule engine 246 and conversion engine 248 may be combined,and may use a single rules database. In further embodiments,configuration agent 232 may be permitted to modify only a subset ofpredetermined rules in the rules database. One example of apredetermined rule may be a rule indicating that a comment tag from alanguage associated with a source installation (“) may be transformed ormodified to a comment tag from a language associated with a targetinstallation (#). Accordingly, in one embodiment of this example,conversion engine 248 may replace comment tags in a source code of anobject responsive to the rule.

As shown, transformer 230 may further comprise an upload engine 250.Upload engine 250, similar to download engine 240, may comprise hardwareand/or software components for uploading or transferring objects tobridge system 202. In some embodiments and as illustrated, upload engine250 may upload converted or transformed automatic code andsemi-automatic code 244A-244B, and may further upload unconverted manualcode 244C. In some embodiments, download engine 240 utilizes an RFC useraccount on solution manager 212 to upload objects, as discussed above.

Solution manager 212 may further comprise a unicode checker 252 and asyntax checker 238B, as shown in FIG. 2C. Unicode checker 252 maycomprise an application, process, agent, function, routine, logic, orany type and form of executable instructions for checking unicodecompliance of a transformed object. Similarly, syntax checker 238B maycomprise an application, process, agent, function, routine, logic, orany type and form of executable instructions for checking objectcompliance with syntax of a language associated with target installation224. In some embodiments, responsive to failure to comply with syntaxand/or unicode, solution manager 212 may present warnings or errors to auser. In other embodiments, responsive to failure to comply with syntaxand/or unicode, solution manager 212 may send the object back toanalysis agent for re-analysis and re-transformation.

Solution manager 212 may comprise a post-processing agent 254.Post-processing agent 254 may comprise an application, process, agent,function, routine, logic, or any type and form of executableinstructions for modifying an object, responsive to instructions from auser interacting with manual conversion agent 234, on configurationclient 210. In some embodiments, manual conversion agent 234 maycomprise an editing application allowing a user to modify source code ofan object, and may include features such as automatic recognition offunctions of a language; display of comments, such as those inserted byanalysis engine 242; and any other features useful to a developer.Although not shown, post-processing agent 254 and manual conversionagent 234 may comprise functionality for communicating over a network toallow a user interacting with configuration client 210 to modify anobject stored on bridge system 202. In an example embodiment, an objectcategorized as manual code 244C may be edited by a user via manualconversion agent 234 and post-processing agent 254 to repair unicode,functions, language features and/or syntax inconsistent with a languageassociated with target installation 224.

Although not illustrated in FIG. 2C, solution manager 212 or bridgesystem 202 may further comprise hardware and/or software components foruploading modified and/or post-processed objects to target installation224.

Referring now to FIG. 2D, illustrated is a block diagram of anembodiment of an analysis and transformation of a source installationinto a target installation. As described above, a source installation220 on source system 204 may be analyzed to create a meta-model 254. Asshown, meta-model 254 may comprise objects, or nodes, and links orstructure representative of dependencies and interactions between nodes.In some embodiments, the meta-model 254 may be transformed intotransformed meta-model 256, responsive to predetermined rules and/orconfigured rules. For example, in a language associated with sourceinstallation 220, a first node representing an function may be dependenton a second node representing an included library of the function.However, in a language associated with target installation 224, thefirst node representing the function may be dependent on both a secondand third node representing two included libraries. Alternately, thefirst node representing the function may, in the language associatedwith the target installation 224 have no dependencies due to explicitinclusion of code in the included library. Accordingly, in this exampleembodiment, transforming the meta-model 254 to transformed meta-model256 may comprise moving the first node representing the function to ahigher level within the abstract syntax tree.

Shown in FIG. 2E is a block diagram of an embodiment of a transformationprocess 258. In brief, an optimization engine 262 may applymodernization rules 260 to create an optimized abstract syntax tree 266.The optimized abstract syntax tree 266 may be further modified by aprogrammer 264 to create target code 270, associated with a targetlanguage syntax dictionary 268. Using test data 272, the target code maybe tested at 274.

Still referring to FIG. 2E and in more detail, modernization rules 260may include a language token or tokens 278, language syntax 282, andsemantic rules 284. A token 278 may be a structured element of code asdefined by the source language. For example, in the expression“print=(hello world);”, tokens 278 include “print”, “=”, “(”, “hello”, “”, “world”, “)”, and “;”. Determining tokens in source code is sometimesreferred to as tokenization or tokenizing, and may, in some embodiments,be performed by lexical analysis engine 280, and configured onoptimization engine 262. In some embodiments, language tokens 278 may becodified and, in some embodiments, stored in a database, dictionary, orother data structure.

Lexical analysis engine 280 may comprise an application, process, agent,function, routine, logic, or any type and form of executableinstructions for locating and interpreting language tokens within sourcecode of an object, as described above.

Language syntax 282 may be a representation of a grammar system within alanguage. A grammar may, in some embodiments, address location andmanipulation of tokens. For example, a token of a semi-colon, used inthe above example, may indicate in a language that it is the end of astatement. Tokens after the semi-colon may apply to the followingstatement, while those before the semi-colon apply to the precedingstatement. Language syntax 282 may, in some embodiments, be stored in adatabase, dictionary, or other data structure. In some embodiments,parser engine 284, configured on optimization engine 262 may use grammaridentified by language syntax 282 to parse tokens identified by lexicalanalysis engine 280. This may be referred to variously as syntacticanalysis, semantic parsing, parsing, or analyzing.

As shown, parser engine 284 may comprise an application, process, agent,function, routine, logic, or any type and form of executableinstructions for interpreting language tokens located in a source codewith language syntax 282 to create an abstract syntax tree 288, alsoreferred to above as a meta-model 254, by applying semantic rules 286.Semantic rules 286 may, in some embodiments, be stored in a database,dictionary or other data structure accessible to parser engine 284. Insome embodiments, parser engine 284 may comprise a top-down parser, suchas a recursive descent parser, or a Left-to-right, Leftmost derivation(LL) parser. In other embodiments, parser engine 284 may comprise abottom-up parser, such as a precedence parser, a bounded context (BC)parser, or a Left-to-right, Rightmost derivation (LR) parser.

Using any of the methods or functions described herein, programmer 264may convert abstract syntax tree 288 to an optimized abstract syntaxtree 266. Programmer 264 may, in some embodiments, comprise part or allof analysis agent 228, discussed in more detail above. Optimizedabstract syntax tree 266 may be a transformed meta-model 256, discussedabove. In some embodiments, optimization of an abstract syntax tree 266may be performed responsive to semantic rules and language syntaxassociated with a target language syntax dictionary 268. Objects of asource installation may be transformed to target code 270, responsive todifferences between the optimized abstract syntax tree 266 and abstractsyntax tree 288.

In some embodiments, test data 272 may be applied to target code 270 fortesting purposes 274. In further embodiments, testing may be performedby a user, while in other embodiments, testing may be performed by aservice or application identifying errors such as buffer overruns,unescaped loops, and other programming errors.

Shown in FIGS. 3A-B is a flow chart, split across two figures forclarity, illustrating an embodiment of a method 302 of analyzing andtransforming an application from a source installation to a targetinstallation. In brief, at step 304, a snapshot is taken of a sourceinstallation. At step 306, a determination is made as to whether thesource installation may be upgraded. If the source installation cannotbe upgraded, the method exits and may, in some embodiments, return anerror or display further instructions. If the source installation may beupgraded, then at step 308, the project is defined and configured. Atstep 310, an object may be downloaded from the source installation. Atstep 312, an identification of the object may be made to determine if ithas been modified from a predetermined state. In some embodiments notillustrated, responsive to a determination that the object has not beenmodified, the object may be discarded, and the method may move to step318, described below. If the object has been modified, then at step 314,the object may be parsed into a set of elements. At step 316, ameta-model may be generated representing the modified object. At step318, a determination may be made as to whether more objects exist in thesource installation. If so, steps 310-318 may be repeated. In someembodiments, repetition of step 316 may comprise modifying a generatedmeta-model to include representations of each additional modified objectparsed during repetitions of step 314.

At step 318, analysis rules may be applied to each element in themeta-model. At step 320, a determination may be made as to thetransformation capability of each object. At step 322, a report may begenerated and, in some embodiments, displayed to a user. At step 324,the user may customize analysis rules. If analysis rules have beencustomized, then steps 318-324 may be repeated. If analysis rules arenot customized at step 324, then at step 326, the meta-model may betransferred to a transformer, discussed above. At step 328,transformation rules may be applied to the meta-model to create atransformed meta-model. At step 330, an object may be modified togenerate a transformed object, responsive to dependencies and rulesassociated with the transformed meta-model. At step 332, a determinationmay be made as to whether more objects exist. If so, steps 330 and 332may be repeated. If not, then at step 334, a comparison report may begenerated comparing transformed objects with their untransformed states.At step 336, a user may customize transformation rules. If the rules arecustomized, then steps 328-336 may be repeated. At step 338, thesnapshot taken at step 304 may be compared with a current state of thesource installation. If the source installation has changed, then steps304-338 may be repeated.

At step 340, transformed objects may be uploaded to the targetinstallation. At step 342, the target installation may bepost-processed, which may comprise making additional manual changes toobjects uploaded to the target installation. At step 344, the targetinstallation may be compiled and/or tested.

Still referring to FIGS. 3A-B and in more detail, at step 304, asnapshot may be taken of a source installation. As described above, insome embodiments, taking a snapshot may comprise storing a copy of oneor more objects of a source installation as they exist at a certaintime. In further embodiments, only part of the source installation maybe snapshotted. For example, in one such embodiment, only customized ormodified objects of the source installation may be snapshotted, to saveanalyzing unnecessary elements.

At step 306, in some embodiments, a determination may be made whetherthe source installation may be upgraded. For example, in one suchembodiment, the source installation may already have been upgraded tothe same version as the target installation, and thus not requireupgrading. In some embodiments, the source installation and targetinstallation may not be compatible for an upgrade. In some embodiments,the system determines the number of changes, issues or non-compliancyexceed a predetermined threshold for upgrading to the target system.

At step 308, the project may be defined and configured. In someembodiments, defining and configuring the project may comprise selectinga version and/or language for a target installation. In additionalembodiments, configuring the project may comprise installing andconfiguring a target installation in a default or predetermined state,lacking customized objects. In a further embodiment, configuring theproject may comprise setting up RFC, Dialog, and Tool user accounts, asdiscussed above.

At step 310, an object may be downloaded from a source installation,using any of the methods and systems described herein, such as acollection agent and a collection plugin. At step 312, the object may beidentified as modified from a predetermined state. In an alternateembodiment not shown, steps 310 and 312 may be reversed, such thatobjects are identified as modified before they are downloaded. Such anembodiment may allow the system to avoid downloading unmodified objects,as discussed above. In some embodiments, identifying an object modifiedfrom a predetermined state may comprise identifying an object that doesnot exist in a source installation. For example, a custom database maynot exist in a default source installation, and accordingly may beconsidered to be a modified object.

At step 314, the object may be parsed into a set of elements, using anyof the methods and systems described herein. For example, an objectsource code may be tokenized and parsed to determine elements andrelationships between elements.

At step 316, a meta-model may be created and/or modified to include theelements and relationships identified at step 314, using any of themethods and systems described above. For example, creating themeta-model may comprise creating an abstract syntax tree representativeof the elements and their interrelationships. The system may generate ameta-model for all the elements of the source installation. In someembodiments, the system may generate a meta-model for a portion ofelements of the source installation, such as the elements identified aschanged from the predetermined state.

At step 318, a determination may be made as to whether more objectsand/or modified objects exist in the source installation, and if so,steps 310-318 may be repeated. In some embodiments, this determinationmay be made by comparing the number of nodes in the meta-model with thenumber of identified objects in the source installation snapshot. Inother embodiments, this determination may be made by failing to locatean additional object or modified object that has not yet been downloadedand parsed.

At step 318, analysis rules may be applied to each element in themeta-model. At step 320, a transformation capability may be determinedfor each object. For example, an object may be classified as automaticcode, semi-automatic code, or manual code, as described above. At step322, a report may be generated. In some embodiments, applying analysisrules comprises performing the functions described above in connectionwith the analysis client and/or analysis engine. In additionalembodiments, generating a report comprises analyzing statistics of thetransformation capability of each object, such as determining ratios ofautomatic, semi-automatic, and manual code, and determining cost and/ortime to perform upgrades, as described above.

At step 324, analysis rules may be customized, and steps 318-324repeated. For example, responsive to determining that upgrading may betoo costly due to a large number of objects to be transformed, a usermay modify analysis rules to exclude a portion of the objects. Steps318-324 may be repeated in some embodiments until the user is satisfiedwith the outcome indicated by the generated report.

At step 326, the meta-model may be transferred to the transformer. Insome embodiments, transferring the model may comprise transmitting themodel to the transformer, while in other embodiments, transferring themodel may comprise the analysis client instructing the transformer toaccess the model on a shared memory element.

At step 328, the transformer may apply transformation rules to themeta-model to generate a transformed meta-model, using any of thesystems and methods discussed herein. In one embodiment, applyingtransformation rules may comprise locating a pattern in the meta-modelcorresponding to an entry in a transformation rule database. In afurther embodiment, applying transformation rules may comprise modifyingan abstract syntax tree according to a rule associated with an entry ina transformation rule database. For example, in one such embodiment, thetransformer may determine that a first element is dependent on a secondelement. The transformer may further determine that the second elementis a function call, such as a WRITE instruction. The transformer maylocate a rule in the rule database associated with target installationlanguage matching a first element dependent on a WRITE instruction, andapply the rule to modify the WRITE instruction to a WRITE TOinstruction.

At step 330, in some embodiments, the transformer may generate atransformed object according to the transformed meta-model. In someembodiments, generating a transformed object comprises modifying asource object. In other embodiments, generating a transformed objectcomprises generating a new object. In one embodiment, a transformedobject may be generated responsive to transformation rules, discussedabove. For example, an object including code representing a WRITEinstruction, as discussed at step 328, may be modified to include coderepresenting a WRITE TO instruction. Further changes may be maderesponsive to transformation rules and/or the transformed meta-model.For example, a first object dependent on a second object in the originalmeta-model may be dependent on a third and fourth object in thetransformed meta-model. Accordingly, at step 330, the transformer mayreplace, in source code of the first object, references to the secondobject with references to the third and/or fourth object. In an exampleof one such embodiment, in a source installation, a first objectcomprising a human resources database, may be dependent on anotherobject comprising an organizational hierarchy. However, in thetransformed meta-model, the human resources database may furthercomprise organizational hierarchy and not be dependent on a secondobject. Accordingly, in this example embodiment, the transformer maymodify the first object to further comprise fields indicating levels andinterconnections previously described in object comprising theorganizational hierarchy. In further embodiments, generating atransformed object may comprise generating an object that possessesdesired characteristics defined by the transformation rules, such asbeing free of syntax violations and/or naming convention errors, or anyother type of characteristic of a source code that may be desired by auser.

At step 332, a determination may be made if more objects exist, usingsimilar methods to those described above at step 318. If so, steps330-332 may be repeated.

At step 334, a comparison report may be generated. In one embodiment, acomparison report comprises a comparison of untransformed elementsand/or objects and transformed elements and/or objects. In a furtherembodiment, the comparison report may be displayed or presented to auser. For example, in an embodiment of the example discussed above atstep 330, a report may be generated showing (a) the first objectcomprising the human resources database with source code showingdependency on the second object comprising the organizational hierarchy;and (b) the first object comprising the human resources database withsource code showing no dependency on the second object, but ratherincluding additional data representing the hierarchical levels andinterconnections. At step 336, the user may customize the transformationrules. In some embodiments, this may be done for increasing efficiency,adjusting for undesired behavior, or any other reason. Referring to theexample discussed above at step 334, a user may decide that it ispreferable to maintain the separate human resources database andorganizational hierarchy, and may adjust the transformation rules toexclude or disable this transformation. In another example, anorganization may be expanding simultaneously with upgrading, and may beadding additional manufacturing locations. In such an example, a usermay modify the transformation rules to incorporate the additionalresources for each new manufacturing location, such as additionalinventory databases, additional shipping locations, or any other typeand form of resource or object. In some embodiments, if the user hascustomized or modified the transformation rules, steps 328-336 may berepeated.

At step 338, the analysis client may determine if the sourceinstallation has changed since the snapshot was taken. This could occur,for example, if analysis, transformation, and customization have taken asignificant amount of time. If so, steps 304-338 may be repeated. Insome embodiments, repeating steps 304-338 may comprise repeating steps304-338 only on objects that have been modified in the sourceinstallation since the previous snapshot. These embodiments may reduceanalysis, transformation, and customization time greatly, as onlyobjects that have changed will need to be re-analyzed and transformed.In further embodiments, transformed objects that have not changed in thesource installation may be stored on a storage element until thedetermination at step 338 indicates that no further changes haveoccurred in the source installation.

Responsive to no further changes having occurred in the sourceinstallation since the previous snapshot was taken, at step 340, theobject transformations may be applied to the target installation. Insome embodiments, applying the transformations may comprise uploading ortransmitting transformed elements and/or objects to the targetinstallation, using any of the methods or systems discussed herein.

At step 342, the target installation may be post-processed. In someembodiments, post-processing the target installation may compriseediting manual or semi-automatic code, as discussed above. In additionalembodiments, post-processing the target installation may compriseoptimizing the installation. For example, optimization may includecompressing the installation, removing unnecessary comments and/or code,cleaning up or removing unused variables, or any other type and form ofsource code optimization.

At step 344, the target installation may be tested. In some embodiments,step 344 may further comprise compiling the target installation. Inother embodiments, the target installation does not require compiling,for example, if all objects are XML objects. In some embodiments,testing the target installation comprises installing test data to thetarget installation, performing modifications to objects and databases,and verifying expected results. In some embodiments, responsive toerrors during testing, one or more steps of method 302 may be repeated,for example steps 328-344.

As discussed above, these methods of using a cloud service forapplication transformation provide both flexibility in deployment andadvantages in parallel and concurrent processing and transformation ofobjects of the application. This may reduce the need for customers ofthe application transformation service to supply local infrastructure,and allow the service to support the needs of multiple customerssimultaneously.

C. Systems and Methods for Dynamically Replacing Code Objects of anApplication for Code Pushdown

As discussed above, a data-to-code paradigm is constrained by passinglarge amounts of data from database servers to application servers, evenfor simple calculations, which creates severe performance bottlenecks.For example, in some instances in which data is filtered by theapplication server before performing further processing, the ratio ofuseful data to total retrieved data may be low. The application servermay even have to retrieve additional data from the database layer inorder to perform the filtering, increasing the volume of data that needsto be transferred to the application layer. By pushing down code ormoving to a code-to-data paradigm, at least for some calculations, thesebottlenecks can be mitigated and performance greatly increased. Inparticular, by taking advantage of improved database architecturecharacteristics, in-memory databases such as SAP HANA can offeroptimized access to data. Calculations that may be appropriate are thosein which the time to transfer necessary input data may approach orexceed processing time, or calculations in which the amount of inputdata greatly exceeds the amount of output data (e g summing largeamounts of data to a single value, counting references in a largedataset to output a single count, aggregating large numbers of recordsto output a set representing the most common data values for a fewvariables, etc.). Code or business logic for performing such functionsmay be moved to the database layer, and processing may be executed bydatabase servers on the data in place, without requiring additionaltransfers and buffering of large amounts of data within the applicationlayer.

In many implementations, pushing down code or transforming code from adata-to-code paradigm to a code-to-data paradigm may require a number oftransformations or modifications to the code. For example, in additionto merely moving executable code from the application servers to thedatabase servers for storage within the database layer, transforming thecode may also require, in some implementations, adding communicationscalls to and from other application layer code. For example, given anapplication under the data-to-code paradigm that, as a subroutine,retrieved a large number of records, calculated a sum of values, andreturned the result for further calculation, pushing down code of theapplication may include transferring the subroutine to the databaselayer and adding a remote procedure call and callback. Similarly, codethat retrieves and returns records to and from the remote databaseservers may be replaced with code that references local storagelocations. Performing these changes and transformations manually may belabor intensive. However, using the systems and methods discussed above,code for pushdown or that interacts with pushed down code may beidentified as automatic or semi-automatic code and quickly modified withlimited human intervention.

Not all code may be appropriate for pushing down to the database layer.For example, code that requires interaction with a user or calls tounmodifiable code may be preferably executed by the application servers.Accordingly, in some implementations, the analyzer client may filter orselect code for pushdown based on analysis of the size of input andoutput data required for transfer in data-to-code paradigms. Forexample, if the amount of input data to an application from the databaselayer is much greater than the amount of output data (e.g. for summing,aggregation, filtering, or similar data operations) provided to otherapplications or to the database layer, the code may be a good candidatefor pushdown. In other implementations, the analyzer client may filteror select code for pushdown based on analysis of the amount of inputdata required and the time to transfer the data from a database serverto and from an application server, compared to the time to process thedata. For example, given a lot of data and a simple processing operation(e.g. concatenating large amounts of data, setting a field of a largenumber of records to a predetermined value, or similar operations,etc.), it may be more efficient to perform the operations at thedatabase servers and the code may be appropriate for pushdown. Once codeis identified for pushdown, references may be replaced and procedurecalls generated accordingly.

Referring now to FIG. 4C, illustrated is a flow chart of animplementation of automated code analysis and pushdown to a databaselayer, or from a data-to-code paradigm to a code-to-data paradigm. Atstep 420, an analyzer client may identify an item of application layercode within a source installation. In some implementations, as discussedabove in connection with FIG. 3, the analyzer client may generate andstore a snapshot of an installation prior to transformation. In someimplementations, the analyzer client may identify an item of applicationlayer code by parsing sections of code for discrete routines orsubroutines containing calls to retrieve and/or store data in thedatabase that may be potentially pushed down.

Once a section of code that retrieves and processes data is identified,in some implementations, at step 422, the analyzer client may determineif a time to transfer the data is equal to or exceeds a time to processthe data. In some implementations, the analyzer client may determine atime to transfer the data based on a size of the data, number ofrecords, complexity of data query, or any other such characteristics. Insome implementations, the analyzer client may further calculate transfertimes based off network interconnection speeds, database read speeds, orother such parameters. Similarly, in some implementations, the analyzerclient may determine a time to process the data based on the number,type, and/or complexity of processing operations to be performed,whether the operations may be parallelized, etc. In someimplementations, if the time to transfer the data does not exceed thetime to process the data, the code may be identified as not to be pusheddown. In a further implementation, the code section may be flagged formanual review at step 426, allowing an operator to potentially overridethe determination. If there is further code to be analyzed at step 436,the analyzer client may repeat step 420.

In some implementations, at step 424, the analyzer client may determinewhether the amount of input data for processing exceeds or is muchlarger than the amount of output data for the section of code.Determining the amount of input data and amount of output data mayinclude, in some implementations, performing test queries or operationson the database and counting the amount of transferred data. In otherimplementations, determining the amount of input data and amount ofoutput data may be based on the type of processing operations to beperformed (e.g. operations summing a large number of values to output asingle result, vs. operations adding an offset to a large number ofvalues and outputting the modified values). In some implementations,determining that the amount of input data is much larger than the amountof data may include determining that the amount of input data is twicethe size of output data, five times the size of output data, ten timesthe size of output data, one hundred times the size of output data, orany other such value. In some implementations, if the amount of inputdata does not greatly exceed the amount of output data, the code may beidentified as not to be pushed down. In a further implementation, thecode section may be flagged for manual review at step 426, allowing anoperator to potentially override the determination. If there is furthercode to be analyzed at step 436, the analyzer client may repeat step420.

Although shown in consecutive order, in some implementations, steps 422and 424 may be performed in parallel. In other implementations, only oneof steps 422 and 424 may be performed. In still other implementations,step 424 may be performed before step 422. In yet still otherimplementations, further filtering operations may be performed to selectcode for transformation.

Once code has been filtered and selected for pushing down, at step 428,in some implementations, a transformer may modify the code by replacingremote references or calls to retrieve data from the database with localreferences or addresses for the data within the database, as opposed toremote procedure calls. In other implementations, the transformer maymodify syntax or parameters of references (e.g. adding local directoryreferences, removing remote directory references, etc.). At step 430,the transformer may generate remote procedure calls to the applicationlayer code to direct the database server to execute the code segment,and may add callbacks to the code to return the appropriate results tothe application layer code. In some implementations, adding remote callsand callbacks may include changing a location of a called sub-routine,while in other implementations, adding remote calls and callbacks mayinclude adding code to generate and transmit requests or queries to thedatabase server and receive a response. At step 432, the transformer maystore the modified code or procedure in the database, and at step 434,the transformer may remove the corresponding code segment from theapplication layer code. In many implementations, the removed code andstored code may comprise a portion of the code segment (e.g. a portionother than remote procedure calls and callbacks). If there is furthercode to be analyzed at step 436, the analyzer client may repeat step420. In some implementations, additional optimization steps may beperformed, such as making code Unicode compliant, applying preconfigureddatabase layer functions (e.g. aggregation or summing, unit of measureconversion, data analysis and prediction, or other such functions, suchas those provided as part of the Business Function Library (BFL) orPredictive Analysis Library (PAL) of SAP HANA), or other such stepsaccording to transformation rules.

Once all code segments have been analyzed and, if appropriate,transformed, then at step 438, the transformer may completetransformation of the target installation and generate one or morereports, as discussed above in connection with FIGS. 2-3.

Accordingly, the systems and methods discussed herein provide automatedanalysis and transformation of a system from a data-to-code to acode-to-data paradigm, moving customized code and business logic from anapplication layer to a database layer for optimized performance.

In one aspect, the present disclosure is directed to a method forautomated code pushdown, or for automated transformation of applicationlayer executable code to execution in a database layer of a businessmanagement system. The method includes identifying, by an analyzerclient executed by a processor of a client device, a first segment ofexecutable code from an application layer of a business managementsystem comprising the application layer and a database layer; anddetermining, by the analyzer client, to transform the first segment ofexecutable code for execution at the database layer of the businessmanagement system. The method also includes modifying, by a transformerexecuted by the processor, the first segment of executable codeaccording to one or more transformation rules; storing, by thetransformer, a first portion of the first segment of executable code atthe database layer of the business management system; and removing, bythe transformer, the first portion of the first segment of executablecode from the application layer of the business management system.

In some implementations, the method includes selecting the first segmentof executable code, responsive to the first segment comprising code toretrieve data from the database layer. In other implementations, themethod includes determining that a time to transfer input data for thefirst segment of executable code exceeds a processing time of the firstsegment of executable code. In a further implementation, the methodincludes determining the time to transfer input data for the firstsegment by performing a test query, by the analyzer client, for theinput data. In another further implementation, the method includesdetermining the processing time of the first segment of executable codebased on the number, type, or complexity of processing operations to beperformed.

In some implementations, the method includes determining to transformthe first segment of executable code further comprises determining thata size of input data for the first segment of executable code exceeds asize of output data from the first segment of executable code. In afurther implementation, the method includes determining the size ofinput data by performing a test query, by the analyzer client, for theinput data. In another further implementation, the method includesdetermining the size of output data based on the type of processingoperation to be performed.

In some implementations, the method includes generating a remoteprocedure call from the application layer to the database layer. In afurther implementation, the method includes generating a callback fromthe database layer to the application layer, responsive to execution ofa portion of the first segment of executable code by a database serverof the business management system.

In another aspect, the present disclosure is directed to a system forautomated code pushdown, or for automated transformation of applicationlayer executable code to execution in a database layer of a businessmanagement system. The system includes a client device in communicationwith a business management system, the client device comprising aprocessor executing an analyzer client and a transformer. The analyzerclient is configured for identifying a first segment of executable codefrom an application layer of a business management system comprising theapplication layer and a database layer, and determining to transform thefirst segment of executable code for execution at the database layer ofthe business management system. The transformer is configured formodifying the first segment of executable code according to one or moretransformation rules, storing a first portion of the first segment ofexecutable code at the database layer of the business management system,and removing the first portion of the first segment of executable codefrom the application layer of the business management system.

In some implementations, the analyzer is further configured forselecting the first segment of executable code, responsive to the firstsegment comprising code to retrieve data from the database layer. Inother implementations, the analyzer is further configured fordetermining that a time to transfer input data for the first segment ofexecutable code exceeds a processing time of the first segment ofexecutable code. In a further implementation, the analyzer is furtherconfigured for determining the time to transfer input data for the firstsegment by performing a test query, by the analyzer client, for theinput data. In another further implementation, the analyzer is furtherconfigured for determining the processing time of the first segment ofexecutable code based on the number, type, or complexity of processingoperations to be performed.

In some implementations, the analyzer is further configured fordetermining that a size of input data for the first segment ofexecutable code exceeds a size of output data from the first segment ofexecutable code. In a further implementation, the analyzer is furtherconfigured for determining the size of input data by performing a testquery, by the analyzer client, for the input data. In another furtherimplementation, the analyzer is further configured for determining thesize of output data based on the type of processing operation to beperformed.

In some implementations, the transformer is further configured forgenerating a remote procedure call from the application layer to thedatabase layer. In a further implementation, the transformer is furtherconfigured for generating a callback from the database layer to theapplication layer, responsive to execution of a portion of the firstsegment of executable code by the database server of the businessmanagement system.

While various embodiments of the methods and systems have beendescribed, these embodiments are exemplary and in no way limit the scopeof the described methods or systems. Those having skill in the relevantart can effect changes to form and details of the described methods andsystems without departing from the broadest scope of the describedmethods and systems. Thus, the scope of the methods and systemsdescribed herein should not be limited by any of the exemplaryembodiments and should be defined in accordance with the accompanyingclaims and their equivalents.

What is claimed:
 1. A method for automated transformation of application layer executable code to execution in a database layer of a business management system, comprising: identifying, by an analyzer client executed by a processor of a client device, a first segment of executable code from an application layer of a business management system comprising the application layer and a database layer; determining, by the analyzer client, to transform the first segment of executable code for execution at the database layer of the business management system; modifying, by a transformer executed by the processor, the first segment of executable code according to one or more transformation rules; storing, by the transformer, a first portion of the first segment of executable code at the database layer of the business management system; and removing, by the transformer, the first portion of the first segment of executable code from the application layer of the business management system.
 2. The method of claim 1, wherein identifying the first segment of executable code further comprises selecting the first segment of executable code, responsive to the first segment comprising code to retrieve data from the database layer.
 3. The method of claim 1, wherein determining to transform the first segment of executable code further comprises determining that a time to transfer input data for the first segment of executable code exceeds a processing time of the first segment of executable code.
 4. The method of claim 3, further comprising determining the time to transfer input data for the first segment by performing a test query, by the analyzer client, for the input data.
 5. The method of claim 3, further comprising determining the processing time of the first segment of executable code based on the number, type, or complexity of processing operations to be performed.
 6. The method of claim 1, wherein determining to transform the first segment of executable code further comprises determining that a size of input data for the first segment of executable code exceeds a size of output data from the first segment of executable code.
 7. The method of claim 6, further comprising determining the size of input data by performing a test query, by the analyzer client, for the input data.
 8. The method of claim 6, further comprising determining the size of output data based on the type of processing operation to be performed.
 9. The method of claim 1, wherein modifying the first segment of executable code according to the one or more transformation rules further comprises generating a remote procedure call from the application layer to the database layer.
 10. The method of claim 9, further comprising generating a callback from the database layer to the application layer, responsive to execution of a portion of the first segment of executable code by a database server of the business management system.
 11. A system for automated transformation of application layer executable code to execution in a database layer of a business management system, comprising: a client device in communication with a business management system, the client device comprising a processor executing an analyzer client and a transformer; wherein the analyzer client is configured for: identifying a first segment of executable code from an application layer of a business management system comprising the application layer and a database layer, and determining to transform the first segment of executable code for execution at the database layer of the business management system; and wherein the transformer is configured for: modifying the first segment of executable code according to one or more transformation rules, storing a first portion of the first segment of executable code at the database layer of the business management system, and removing the first portion of the first segment of executable code from the application layer of the business management system.
 12. The system of claim 11, wherein the analyzer is further configured for selecting the first segment of executable code, responsive to the first segment comprising code to retrieve data from the database layer.
 13. The system of claim 11, wherein the analyzer is further configured for determining that a time to transfer input data for the first segment of executable code exceeds a processing time of the first segment of executable code.
 14. The system of claim 13, wherein the analyzer is further configured for determining the time to transfer input data for the first segment by performing a test query, by the analyzer client, for the input data.
 15. The system of claim 13, wherein the analyzer is further configured for determining the processing time of the first segment of executable code based on the number, type, or complexity of processing operations to be performed.
 16. The system of claim 11, wherein the analyzer is further configured for determining that a size of input data for the first segment of executable code exceeds a size of output data from the first segment of executable code.
 17. The system of claim 16, wherein the analyzer is further configured for determining the size of input data by performing a test query, by the analyzer client, for the input data.
 18. The system of claim 16, wherein the analyzer is further configured for determining the size of output data based on the type of processing operation to be performed.
 19. The system of claim 11, wherein the transformer is further configured for generating a remote procedure call from the application layer to the database layer.
 20. The system of claim 19, wherein the transformer is further configured for generating a callback from the database layer to the application layer, responsive to execution of a portion of the first segment of executable code by the database server of the business management system. 